2025-11-01
Large reasoning models almost certainly can think
Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of Thinking" Apple argues that LRMs must not be able to think; instead, they just perform pattern-matching. The evidence they provided is that LRMs with chain-of-thought (CoT) reasoning are unable to carry on the calculation using a predefined algorithm as the problem grows.
This is a fundamentally flawed argument. If you ask a human who already knows the algorithm for solving the Tower-of-Hanoi problem to so [...]
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2025-11-17
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
2025-12-02
New training method boosts AI multimodal reasoning with smaller, smarter datasets
Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]
2025-10-08
Samsung AI researcher's new, open reasoning model TRM outperforms models 10,000X larger — on specific problems
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2025-02-28
Engadget Podcast: iPhone 16e review and Amazon's AI-powered Alexa+
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2025-11-14
Google’s new AI training method helps small models tackle complex reasoning
Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning task [...]
2025-10-30
Meta researchers open the LLM black box to repair flawed AI reasoning
Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its [...]
2025-10-09
Nvidia researchers boost LLMs reasoning skills by getting them to 'think' during pre-training
Researchers at Nvidia have developed a new technique that flips the script on how large language models (LLMs) learn to reason. The method, called reinforcement learning pre-training (RLP), integrates [...]
2025-11-06
Moonshot's Kimi K2 Thinking emerges as leading open source AI, outperforming GPT-5, Claude Sonnet 4.5 on key benchmarks
Even as concern and skepticism grows over U.S. AI startup OpenAI's buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has e [...]
2025-12-09
Z.ai debuts open source GLM-4.6V, a native tool-calling vision model for multimodal reasoning
Chinese AI startup Zhipu AI aka Z.ai has released its GLM-4.6V series, a new generation of open-source vision-language models (VLMs) optimized for multimodal reasoning, frontend automation, and high-e [...]